Scientific discovery in the age of artificial intelligence

Deep learning-guided discovery of an antibiotic targeting Acinetobacter baumannii

(2023) Gary Liu et al.   Nature Chemical Biology

Graph neural networks at the Large Hadron Collider

(2023) Gage DeZoort et al.   Nature Reviews Physics

Magnetic control of tokamak plasmas through deep reinforcement learning

(2022) Jonas Degrave et al.   NATURE

Using deep learning to annotate the protein universe

(2022) Maxwell L. Bileschi et al.   NATURE BIOTECHNOLOGY

Reducing adverse impacts of Amazon hydropower expansion

(2022) Alexander S. Flecker et al.   SCIENCE

Accelerated identification of disease-causing variants with ultra-rapid nanopore genome sequencing

(2022) Sneha D. Goenka et al.   NATURE BIOTECHNOLOGY

ColabFold: making protein folding accessible to all

(2022) Milot Mirdita et al.   NATURE METHODS

Machine Learning Hidden Symmetries

(2022) Ziming Liu et al.   PHYSICAL REVIEW LETTERS

Adaptive Monte Carlo augmented with normalizing flows

(2022) Marylou Gabrié et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

Autonomous platforms for data-driven organic synthesis

(2022) Wenhao Gao et al.   Nature Communications

Learning meaningful representations of protein sequences

(2022) Nicki Skafte Detlefsen et al.   Nature Communications

A cost-aware framework for the development of AI models for healthcare applications

(2022) Gabriel Erion et al.   Nature Biomedical Engineering

Evidence for intrinsic charm quarks in the proton

(2022) et al.   NATURE

Informing geometric deep learning with electronic interactions to accelerate quantum chemistry

(2022) Zhuoran Qiao et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

Digitization and validation of a chemical synthesis literature database in the ChemPU

(2022) Simon Rohrbach et al.   SCIENCE

Language models can learn complex molecular distributions

(2022) Daniel Flam-Shepherd et al.   Nature Communications

Artificial intelligence foundation for therapeutic science

(2022) Kexin Huang et al.   Nature Chemical Biology

Multimodal biomedical AI

(2022) Julián N. Acosta et al.   NATURE MEDICINE

Inductive biases for deep learning of higher-level cognition

(2022) Anirudh Goyal et al.   PROCEEDINGS OF THE ROYAL SOCIETY A-MATHEMATICAL PHYSICAL AND ENGINEERING SCIENCES

Hallucinating symmetric protein assemblies

(2022) B. I. M. Wicky et al.   SCIENCE

Graph representation learning in biomedicine and healthcare

(2022) Michelle M. Li et al.   Nature Biomedical Engineering

Evaluation and development of deep neural networks for image super-resolution in optical microscopy

(2021) Chang Qiao et al.   NATURE METHODS

Estimation of Thermodynamic Observables in Lattice Field Theories with Deep Generative Models

(2021) Kim A. Nicoli et al.   PHYSICAL REVIEW LETTERS

Learning the language of viral evolution and escape

(2021) Brian Hie et al.   SCIENCE

Machine learning in combinatorial polymer chemistry

(2021) Adam J. Gormley et al.   Nature Reviews Materials

TorchMD: A Deep Learning Framework for Molecular Simulations

(2021) Stefan Doerr et al.   Journal of Chemical Theory and Computation

The data-driven future of high-energy-density physics

(2021) Peter W. Hatfield et al.   NATURE

Low-N protein engineering with data-efficient deep learning

(2021) Surojit Biswas et al.   NATURE METHODS

Toward Causal Representation Learning

(2021) Bernhard Scholkopf et al.   PROCEEDINGS OF THE IEEE

Machine learning–accelerated computational fluid dynamics

(2021) Dmitrii Kochkov et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

Network medicine framework for identifying drug-repurposing opportunities for COVID-19

(2021) Deisy Morselli Gysi et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

Biological structure and function emerge from scaling unsupervised learning to 250 million protein sequences

(2021) Alexander Rives et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

Bias free multiobjective active learning for materials design and discovery

(2021) Kevin Maik Jablonka et al.   Nature Communications

Quantitative interpretation explains machine learning models for chemical reaction prediction and uncovers bias

(2021) Dávid Péter Kovács et al.   Nature Communications

Open Catalyst 2020 (OC20) Dataset and Community Challenges

(2021) Lowik Chanussot et al.   ACS Catalysis

Artificial Intelligence in Chemistry: Current Trends and Future Directions

(2021) Zachary J. Baum et al.   Journal of Chemical Information and Modeling

Stiff-PINN: Physics-Informed Neural Network for Stiff Chemical Kinetics

(2021) Weiqi Ji et al.   JOURNAL OF PHYSICAL CHEMISTRY A

Highly accurate protein structure prediction with AlphaFold

(2021) John Jumper et al.   NATURE

Swarm Learning for decentralized and confidential clinical machine learning

(2021) Stefanie Warnat-Herresthal et al.   NATURE

Geometric deep learning of RNA structure

(2021) Raphael J. L. Townshend et al.   SCIENCE

Accurate prediction of protein structures and interactions using a three-track neural network

(2021) Minkyung Baek et al.   SCIENCE

Turn-key constrained parameter space exploration for particle accelerators using Bayesian active learning

(2021) Ryan Roussel et al.   Nature Communications

Mapping the multiscale structure of biological systems

(2021) Leah V. Schaffer et al.   Cell Systems

GANplifying event samples

(2021) Anja Butter et al.   SciPost Physics

Datasheets for datasets

(2021) Timnit Gebru et al.   COMMUNICATIONS OF THE ACM

PINNeik: Eikonal solution using physics-informed neural networks

(2021) Umair bin Waheed et al.   COMPUTERS & GEOSCIENCES

The Open Reaction Database

(2021) Steven M. Kearnes et al.   JOURNAL OF THE AMERICAN CHEMICAL SOCIETY

Synthon-based ligand discovery in virtual libraries of over 11 billion compounds

(2021) Arman A. Sadybekov et al.   NATURE

Biologically informed deep neural network for prostate cancer discovery

(2021) Haitham A. Elmarakeby et al.   NATURE

A multi-scale map of cell structure fusing protein images and interactions

(2021) Yue Qin et al.   NATURE

Advancing mathematics by guiding human intuition with AI

(2021) Alex Davies et al.   NATURE

De novo protein design by deep network hallucination

(2021) Ivan Anishchenko et al.   NATURE

Multi-omic machine learning predictor of breast cancer therapy response

(2021) Stephen-John Sammut et al.   NATURE

Super-resolved spatial transcriptomics by deep data fusion

(2021) Ludvig Bergenstråhle et al.   NATURE BIOTECHNOLOGY

Sparse deconvolution improves the resolution of live-cell super-resolution fluorescence microscopy

(2021) Weisong Zhao et al.   NATURE BIOTECHNOLOGY

Multiscale and integrative single-cell Hi-C analysis with Higashi

(2021) Ruochi Zhang et al.   NATURE BIOTECHNOLOGY

Effective gene expression prediction from sequence by integrating long-range interactions

(2021) Žiga Avsec et al.   NATURE METHODS

Bayesian parameter estimation using conditional variational autoencoders for gravitational-wave astronomy

(2021) Hunter Gabbard et al.   Nature Physics

The LHC Olympics 2020 a community challenge for anomaly detection in high energy physics

(2021) Gregor Kasieczka et al.   REPORTS ON PROGRESS IN PHYSICS

Autonomous materials synthesis via hierarchical active learning of nonequilibrium phase diagrams

(2021) Sebastian Ament et al.   Science Advances

A Deep Learning Approach to Antibiotic Discovery

(2020) Jonathan M. Stokes et al.   CELL

Realistic in silico generation and augmentation of single-cell RNA-seq data using generative adversarial networks

(2020) Mohamed Marouf et al.   Nature Communications

Delegated Regressor, A Robust Approach for Automated Anomaly Detection in the Soil Radon Time Series Data

(2020) Muhammad Rafique et al.   Scientific Reports

A Bayesian machine scientist to aid in the solution of challenging scientific problems

(2020) Roger Guimerà et al.   Science Advances

The Synthesizability of Molecules Proposed by Generative Models

(2020) Wenhao Gao et al.   Journal of Chemical Information and Modeling

Unveiling the predictive power of static structure in glassy systems

(2020) V. Bapst et al.   Nature Physics

OmniFold: A Method to Simultaneously Unfold All Observables

(2020) Anders Andreassen et al.   PHYSICAL REVIEW LETTERS

Large scale active-learning-guided exploration for in vitro protein production optimization

(2020) Olivier Borkowski et al.   Nature Communications

Accurate Multiobjective Design in a Space of Millions of Transition Metal Complexes with Neural-Network-Driven Efficient Global Optimization

(2020) Jon Paul Janet et al.   ACS Central Science

Understanding, Values, and the Aims of Science

(2020) Henk Willem de Regt   PHILOSOPHY OF SCIENCE

Earthquake transformer—an attentive deep-learning model for simultaneous earthquake detection and phase picking

(2020) S. Mostafa Mousavi et al.   Nature Communications

Annotation-free learning of plankton for classification and anomaly detection

(2020) Vito P. Pastore et al.   Scientific Reports

Interpretability of machine learning‐based prediction models in healthcare

(2020) Gregor Stiglic et al.   Wiley Interdisciplinary Reviews-Data Mining and Knowledge Discovery

A framework for adaptive MCMC targeting multimodal distributions

(2020) Emilia Pompe et al.   ANNALS OF STATISTICS

Deep-neural-network solution of the electronic Schrödinger equation

(2020) Jan Hermann et al.   Nature Chemistry

Minimum information about clinical artificial intelligence modeling: the MI-CLAIM checklist

(2020) Beau Norgeot et al.   NATURE MEDICINE

MARS: discovering novel cell types across heterogeneous single-cell experiments

(2020) Maria Brbić et al.   NATURE METHODS

Equivariant Flow-Based Sampling for Lattice Gauge Theory

(2020) Gurtej Kanwar et al.   PHYSICAL REVIEW LETTERS

Transfer learning enables the molecular transformer to predict regio- and stereoselective reactions on carbohydrates

(2020) Giorgio Pesciullesi et al.   Nature Communications

Autonomous navigation of stratospheric balloons using reinforcement learning

(2020) Marc G. Bellemare et al.   NATURE

On-the-fly closed-loop materials discovery via Bayesian active learning

(2020) A. Gilad Kusne et al.   Nature Communications

EikoNet: Solving the Eikonal Equation With Deep Neural Networks

(2020) Jonathan D. Smith et al.   IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING

Single-cell RNA-seq denoising using a deep count autoencoder

(2019) Gökcen Eraslan et al.   Nature Communications

Adversarial attacks on medical machine learning

(2019) Samuel G. Finlayson et al.   SCIENCE

Deep learning and process understanding for data-driven Earth system science

(2019) Markus Reichstein et al.   NATURE

GuacaMol: Benchmarking Models for de Novo Molecular Design

(2019) Nathan Brown et al.   Journal of Chemical Information and Modeling

Interpretable Deep Learning for Spatial Analysis of Severe Hailstorms

(2019) David John Gagne et al.   MONTHLY WEATHER REVIEW

Unsupervised word embeddings capture latent knowledge from materials science literature

(2019) Vahe Tshitoyan et al.   NATURE

Joint analysis of heterogeneous single-cell RNA-seq dataset collections

(2019) Nikolas Barkas et al.   NATURE METHODS

Optimization of Molecules via Deep Reinforcement Learning

(2019) Zhenpeng Zhou et al.   Scientific Reports

Deep learning enables rapid identification of potent DDR1 kinase inhibitors

(2019) Alex Zhavoronkov et al.   NATURE BIOTECHNOLOGY

A robotic platform for flow synthesis of organic compounds informed by AI planning

(2019) Connor W. Coley et al.   SCIENCE

Boltzmann generators: Sampling equilibrium states of many-body systems with deep learning

(2019) Frank Noé et al.   SCIENCE

BigSMILES: A Structurally-Based Line Notation for Describing Macromolecules

(2019) Tzyy-Shyang Lin et al.   ACS Central Science

Autonomous discovery in the chemical sciences part II: Outlook

(2019) Connor W Coley et al.   ANGEWANDTE CHEMIE-INTERNATIONAL EDITION

Deciphering interaction fingerprints from protein molecular surfaces using geometric deep learning

(2019) P. Gainza et al.   NATURE METHODS

Jet substructure at the Large Hadron Collider

(2019) Roman Kogler et al.   REVIEWS OF MODERN PHYSICS

Coarse-graining auto-encoders for molecular dynamics

(2019) Wujie Wang et al.   npj Computational Materials

Recovering Gene Interactions from Single-Cell Data Using Data Diffusion

(2018) David van Dijk et al.   CELL

Deep Potential Molecular Dynamics: A Scalable Model with the Accuracy of Quantum Mechanics

(2018) Linfeng Zhang et al.   PHYSICAL REVIEW LETTERS

Active learning machine learns to create new quantum experiments

(2018) Alexey A. Melnikov et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

Automatic Chemical Design Using a Data-Driven Continuous Representation of Molecules

(2018) Rafael Gómez-Bombarelli et al.   ACS Central Science

Planning chemical syntheses with deep neural networks and symbolic AI

(2018) Marwin H. S. Segler et al.   NATURE

Inverse molecular design using machine learning: Generative models for matter engineering

(2018) Benjamin Sanchez-Lengeling et al.   SCIENCE

Explainable machine-learning predictions for the prevention of hypoxaemia during surgery

(2018) Scott M. Lundberg et al.   Nature Biomedical Engineering

Dimensionality reduction for visualizing single-cell data using UMAP

(2018) Etienne Becht et al.   NATURE BIOTECHNOLOGY

Realizing private and practical pharmacological collaboration

(2018) Brian Hie et al.   SCIENCE

Physics-informed neural networks: A deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations

(2018) M. Raissi et al.   JOURNAL OF COMPUTATIONAL PHYSICS

Geometric Deep Learning: Going beyond Euclidean data

(2017) Michael M. Bronstein et al.   IEEE SIGNAL PROCESSING MAGAZINE

Mastering the game of Go without human knowledge

(2017) David Silver et al.   NATURE

A gravitational-wave standard siren measurement of the Hubble constant

(2017) B. P. Abbott et al.   NATURE

Solving the quantum many-body problem with artificial neural networks

(2017) Giuseppe Carleo et al.   SCIENCE

ANI-1: an extensible neural network potential with DFT accuracy at force field computational cost

(2017) J. S. Smith et al.   Chemical Science

A recurrent neural network for classification of unevenly sampled variable stars

(2017) Brett Naul et al.   Nature Astronomy

Design of efficient molecular organic light-emitting diodes by a high-throughput virtual screening and experimental approach

(2016) Rafael Gómez-Bombarelli et al.   NATURE MATERIALS

Discovering governing equations from data by sparse identification of nonlinear dynamical systems

(2016) Steven L. Brunton et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

Probabilistic machine learning and artificial intelligence

(2015) Zoubin Ghahramani   NATURE

Deep learning

(2015) Yann LeCun et al.   NATURE

Reinforcement learning improves behaviour from evaluative feedback

(2015) Michael L. Littman   NATURE

Machine learning: Trends, perspectives, and prospects

(2015) M. I. Jordan et al.   SCIENCE

Jet-images: computer vision inspired techniques for jet tagging

(2015) Josh Cogan et al.   JOURNAL OF HIGH ENERGY PHYSICS

A large-scale evaluation of computational protein function prediction

(2013) Predrag Radivojac et al.   NATURE METHODS

Lab hazard

(2009) Amber Dance   NATURE

The Automation of Science

(2009) Ross D. King et al.   SCIENCE

Distilling Free-Form Natural Laws from Experimental Data

(2009) Michael Schmidt et al.   SCIENCE